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Full Professorship in Explainable Artificial Intelligence
Full Professor in Explainable Artificial Intelligence
The Department of Data Science and Knowledge Engineering is happy to welcome a full professor who will work on AI systems that can explain, in a human-understandable way, their decisions, actions and recommendations.
We are the Department of Data Science and Knowledge Engineering (DKE) at Maastricht University, the Netherlands: an international community of ~50 researchers at various
stages of their career, embedded in the Faculty of Science and Engineering (FSE). Our department has nearly 30 years' experience with research and teaching in the fields of
Artificial Intelligence, Computer Science and Mathematics, and we do so in a highly collaborative and cross-disciplinary manner. To strengthen our team, we are looking for a
full professor who will work on AI systems that are able to explain the decisions and actions they recommend or take in a human-understandable way.
We are happy to hear how you would implement your personal skill set towards researching explainable AI, and any ideas you may have for filling this position.
One potential focus, which we believe to complement existing research in the department, is to work on integrating the "sub-symbolic" and "symbolic" paradigms of AI. Traditionally, these two paradigms have been investigated separately. The "sub-symbolic" (neural-network-type) paradigm typically leads to systems that show impressive generalization capabilities, yet lack human understandability. On the other hand, the "symbolic" (symbolic-reasoning-type) paradigm tends to lead to systems that can explain (to some degree) their behavior in a human-understandable way, but are limited in their adaptability and flexibility. With the rapidly increasing importance of AI for business and society, the integration of "symbol-level explainability" and "sub-symbolic generalizability" becomes highly crucial.
This position is expected to build on, and benefit from,
foundational expertise at DKE in machine learning (including deep learning, reinforcement learning and relational learning) and automated symbolic reasoning (including diagnostic reasoning, argumentation and search). Our research centers around nine established themes, which includes the theme 'Explainable and Reliable Artificial Intelligence'. Researchers typically work on multiple themes at the same time to ensure knowledge transfer across (sub)disciplines. Outside of the department, we offer an extensive, worldwide network of collaborators in the public and private sector, as well as a firm rooting in national and international AI networks. Facilities include access to a supercomputer cluster and a robotics laboratory.
If desired, we are open to exploring the possibility of bringing your current staff members with you to Maastricht University.
We seek a colleague who is passionate about advancing safe and reliable applications of AI through their research on explainability, and who enjoys communicating developments in this field to our students. She/he feels at home in a strongly international and diverse community like ours. Furthermore, we are happy to welcome someone who fosters collaboration at all levels: from working on small-scale projects with direct colleagues, to participating in international research consortia.
We invite applications from candidates who meet the following requirements:
A PhD in a relevant field, such as Artificial Intelligence;
A strong track record in research at an internationally competitive level;
Proven success in funding acquisition at the national and/or European level;
Extensive experience with supervising PhD students;
Enthusiasm to substantially contribute to the development of our department;
Fluency in English.
CONDITIONS OF EMPLOYMENT
We offer a full-time professorship starting as soon as possible. The nature of your initial appointment depends on your qualifications and track record, and may either be permanent or temporary with the intention of permanent appointment upon a mutually positive assessment. We offer a competitive salary for a position of 38 hours a week. On top of your annual salary, there is an annual holiday allowance (8% of annual income) and an annual end-of-year bonus (8.3% of annual income).
The position comes with a number of additional benefits, including:
Partially paid parental leave;
A pension scheme;
The option to participate in collective healthcare insurance;
A one-time reimbursement of your relocation costs if you are moving to Maastricht from more than 40 kilometers away;
Assistance with practical matters such as housing for candidates unfamiliar with the Netherlands, through Maastricht University's Knowledge Centre for International Staff;
A welcoming and open work environment with a high degree of flexibility, and plenty of opportunities for collaboration and growth;
Mentoring to develop yourself as a teacher and obtain a University Teaching Qualification (BKO, for 'basiskwalificatie onderwijs': an official certification for teaching at Dutch universities) through a training programme, in case you are not yet certified.
Full conditions of employment are laid out in the Collective Labour Agreement of Dutch Universities, supplemented with local UM provisions. For more information look at the website
www.maastrichtuniversity.nl > Support > UM employees.
Furthermore, applicants from outside the Netherlands may be eligible for the so-called 30% ruling, a tax cut for highly skilled migrants that applies for a maximum of five years.
Maastricht University | Maastricht University (UM) has around 18,000 students and 4,300 employees. Reflecting the university's strong international profile, a fair amount of both students and staff are from abroad. Research at UM is characterized by a multidisciplinary and thematic approach, and is concentrated in research institutes and schools. UM is renowned for its unique, innovative, problem-based learning system, which is characterized by a small-scale and student-oriented approach. UM placed #10 in Times Higher Education's (THE) Young Universities Ranking 2019, and #127 in THE's World University Rankings 2020.
Living and working in Maastricht | The Department of Data Science and Knowledge Engineering is housed in the historical city of Maastricht, the Netherlands. Situated in the heart of Europe and within 30 kilometers from the German and Belgian borders, Maastricht and its 120,000 inhabitants have a strong international character. It is a safe and family-friendly city with a history spanning more than 2,000 years. The city's rich past is reflected everywhere in the streets: the ratio of monuments-to-inhabitants is roughly 1:73.
The Department of Data Science and Knowledge Engineering | Founded in 1992, we are a fast-growing department undertaking internationally respected research in the areas of artificial intelligence, data science, computer science and applied mathematics. Much of our research takes place at the interfaces of these disciplines. We maintain a large network of industry partners and provide education through one bachelor's programme and two master's programmes, all of which have a strong focus on Artificial Intelligence and are nationally ranked #1 in their cohort according to the most recent education rankings.
Our new colleague will be joining a tight-knit department consisting of ~50 principal investigators, postdocs and PhD students, nearly 600 BSc and MSc students and a team of 13 dedicated support staff members. Together, we come from over 40 different countries.
STEM research in Maastricht | DKE is embedded in the equally thriving Faculty of Science and Engineering. It's exciting times for STEM research in the region of Zuid-Limburg, where Maastricht University (UM) is situated. For example, UM recently joined the Einstein Telescope Partnership coalition, which will bring STEM challenges to our doorstep through construction of the ETpathfinder prototype gravitational wave detector. Furthermore, Zuid-Limburg is a hub for the high-tech industry. Maastricht University participates in the four regional Brightlands campuses: local tech ecosystems where fundamental and applied research, state-of-the-art facilities, industry partners and students meet. In addition, the university itself offers no shortage of inspiring collaborators through our international network and the five other faculties of UM.
We strongly believe in diversity (including but not limited to nationality, age and gender) and encourage you to apply if you are qualified for this position.
The position will remain open until filled. Depending on your current location, you may be invited for an interview via Skype or in person. To apply for the position, submit the following documents via Academic Transfer:
A cover letter explaining your motivation, your relevant experience and suitability for the position;
A detailed Curriculum Vitae (including a list of publications and key achievements in research).
We are happy to answer any questions you have about the position or our department. You can direct questions to:
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